The year 2022- An era where machines are smart, AI can repair itself and robots can write. Discussions around AI reaching human-level intelligence in the future can be seen everywhere today. As predicted by Google CEO, Sundar Pichai, AI is going to be more transformative to humans than fire and electricity in the future. With AI taking such huge leaps in development and scope, it does not come as a surprise that AI has a huge role to play in marketing and advertising. As social media platforms are evolving into one of the most used mediums through which marketing and advertising campaigns are deployed by brands, involving technology has become imperative. As of today, around 73% of the entire marketing budget of a business gets invested in digital marketing activities. With technology claiming such huge stakes in this department, two important terms- MarTech and AdTech are seen gaining acceptance amongst businesses.
What is MarTech?
With 8000+ MarTech solutions existent today, this term has marketers hooked on the success stories it curates. MarTech refers to Marketing technologies that assist in scaling promotional campaigns and related activities of a brand or a business. By using technology to leverage the power of data, insights into customer profiles, market trends, and resource availability of a business can be done to formulate strategies that are low on budget, less time-consuming, and successful.
For Ben & Jerry’s, Unilever has been using AI data centres from all around the world to gather information from different places. This includes CRM and traditional marketing research. Using AI, Unilever launched a campaign for Ben & Jerry’s known as ice cream for breakfast where they introduced cereal-flavoured ice creams to its customers. For that, Unilever took inspiration from datasets revolving around various song lyrics that had ice cream-breakfast references to identify that ice cream and breakfast can go hand in hand and could prove to be a profitable strategy.
What is AdTech?
Advertising technologies help advertisers control ad spending by being able to personalize and target a specific audience with content that is relatable only to them. This increases sales and conversion rates. Tech-based advertising strategies help measure success and failure and re-plan and re-execute solutions by curbing the loss of resources.
AI: Putting the ‘tech’ in MarTech and AdTech
AI is a technology that can be seen leading the different phases of marketing and advertising campaigns in businesses today. The major use cases are:
Attribution AI:
Conducting business in an era that has people surrounded by n number of options for everything requires great planning and execution. Brands today rely on omnichannel marketing and advertising solutions. There is variation in the types of channels through which people buy products or avail services and acing every medium has become essential for a brand. AI plays a pivotal role in marketing attribution which is extremely important to analyze the effect of the overall campaign on the ROI. Attribution AI is a process that helps a brand analyze the impact of customer interactions against specified outcomes. As compared to the traditional marketing attribution models, Attribution AI models use data-driven approaches that are custom to the brand while setting parameters for varying touchpoints rather than relying on a predefined set of rules. In traditional marketing attribution, a brand may many times not be able to relate to the set of rules and act on incorrect results. Attribution AI helps eliminate bias and produces results that are of use to the business.
Content Creation:
From conceptualization to the actual creation, having content that is ready to go out for the world to see is a time-consuming and resource-intensive process. Various factors hamper creativity and sometimes meeting deadlines becomes a task. This is where Generative Adversarial Networks (GANs) come into the picture. Seen as the creative side of artificial intelligence, GANs are capable of developing, generating, and rectifying content. This innovation can create practical visual outcomes, from photographs to recordings to 3D models to be utilized for marketing and promotional purposes. Some impressive examples of GAN are converting a photo to its emoji and text-to-image translation.
Sentiment analysis and natural language processing:
Sentiment analysis uses analyzers to evaluate emotions and context through text or speech that comes with AI chatbots and virtual avatars nowadays. Digital humans deployed as virtual influencers rank number 1 on the list of most popular marketing tactics today. They have the ability to converse with people in their natural language and these digital humans convey brand essence with a touch of relatability to the customer with the help of NLP. Digital humans bring a digital space like the Metaverse to life and using sentiment analysis, these humans ensure there is empathy in digital conversations with customers, just like its human counterpart in the real world. Digital humans can promote the products and services of a brand irrespective of time and location, without any human intervention. AI-powered virtual influencers can build customer profiles for the brand to create personalized experiences by studying behavioural patterns and understanding preferences.
Contextual targeting:
Contextual targeting refers to the placement of advertising items or a product catalogue on display that is directly relevant to the item being promoted in the ad. In simple terms? Surfing on the internet for hair oil and seeing a section of advertisements or popups from brands selling hair shampoo and conditioner. This is done by coordinating the keywords within the search query to the content within the advertisement. As people are getting apprehensive about the use of cookies as they invade their privacy, contextual advertising is getting more and more relevant as a safer option that keeps user data secure. For this, MarTech solutions and tools saddle the control of computer vision to understand what’s within the pictures and determine the environment from it.
For example, It would be profitable to advertise UAE tourism next to an ad of a car off-roading in the sand dunes.
Customer feedback:
Gathering feedback from the user is crucial for the success of any brand campaign. Various AdTech tools come with AI-powered trackers that help analyze what the user feels about the activity they just saw, read, clicked upon, or engaged in. Trackers are used to see which link or button the user is clicking on the most and which page or section is being revisited. Eye tracking tools help understand at what instance the users show interest in the ad and then relevant content and offers are created for a specific group of people.
Metaverse:
When it comes to Metaverse and marketing, promotional campaigns can be deployed as special artifacts, digital humans, pictures, or videos that are infused into immersive situations on behalf of the brand. AI will help personalize VPPs (virtual product placements) according to the customer profile. VPP is a simulated product, service, or activity projected in an immersive world or the Metaverse on behalf of the brand. It is a part of the environment but these VPPs could differ from user to user in terms of content, placement, and time.
For example: If the system knows that the person walking in the Metaverse is a fashionista, then that person can be shown an advertisement from a luxury brand displaying its latest collection. People who do not fall under the “fashionista” tag will not be shown this advertisement but will be shown an advertisement from a brand selling products they are interested in.
Predictive analysis:
With almost every real-world activity being imitated in the digital world today, the physical footprint is being replaced by the digital footprint of a person that consists of data. A single person is known to generate around 1.75MB of data every second. The availability of data in the world today has reached zettabytes and this data can be used to enhance the efficiency of marketing and advertising with the help of technology. Here’s how: AI can be used to analyze user navigation on a platform by collecting activity log data. As the system has basic details on the user, AI can help create customer profiles and profiles with similar characteristics can be placed in one single group to be the target audience. When the user visits again predictive analysis will help the system dig out the old information and suggest products, content, and services based on what the user would be interested in.
As the dependence of a business on the digital realm increases day by day, The use of AI has become necessary to construct strategies that are not just smart but also empathetic. AI can offer assistance and construct more viable promoting techniques, help make strides in digital experience strategies, and alter the way businesses draw in, sustain, and evolve over customers and the demands of the market. AI and machine learning can be consolidated into each step within the customer’s lifecycle to create a lasting impact and witness active participation from the audience.
About the Author:
Jui Bagul works as an Executive Content Writer at DaveAI. She specializes in writing tech articles. With a Masters degree in Computer Applications, her immense knowledge in the field of technology and love for writing helps her create significant pieces of content.
